Related papers: Towards Provably Safe Mixed Transportation Systems…
Traffic congestion is a major challenge in modern urban settings. The industry-wide development of autonomous and automated vehicles (AVs) motivates the question of how can AVs contribute to congestion reduction. Past research has shown…
It is recognized that the control of mixed-autonomy platoons comprising connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) can enhance traffic flow. Among existing methods, Multi-Agent Reinforcement Learning (MARL)…
As autonomous vehicles (AVs) become increasingly prevalent, their interaction with human drivers presents a critical challenge. Current AVs lack social awareness, causing behavior that is often awkward or unsafe. To combat this, social AVs,…
In this paper, a cooperative decision-making is presented, which is suitable for intention-aware automated vehicle functions. With an increasing number of highly automated and autonomous vehicles on public roads, trust is a very important…
Human-driven vehicles (HVs) amplify naturally occurring perturbations in traffic, leading to congestion--a major contributor to increased fuel consumption, higher collision risks, and reduced road capacity utilization. While previous…
Navigating automated driving systems (ADSs) through complex driving environments is difficult. Predicting the driving behavior of surrounding human-driven vehicles (HDVs) is a critical component of an ADS. This paper proposes an enhanced…
Connected autonomous vehicles (CAVs) can supplement the information from their own sensors with information from surrounding CAVs for decision making and control. This has the potential to improve traffic efficiency. CAVs face additional…
Connected automated vehicles (CAV), which incorporate vehicle-to-vehicle (V2V) communication into their motion planning, are expected to provide a wide range of benefits for individual and overall traffic flow. A frequent constraint or…
We demonstrate a new capability of automated vehicles: mixed autonomy traffic control. With this new capability, automated vehicles can shape the traffic flows composed of other non-automated vehicles, which has the promise to improve…
In the coming years, transportation system will be revamped in a manner that there will be more intelligent and autonomous vehicle phenomenon around us such as smart cars, auto driving system, etc. Some of automotive industries are already…
Connected and automated vehicles (CAVs) are expected to reshape traffic flow dynamics and present new challenges and opportunities for traffic flow modeling. While numerous studies have proposed optimal modeling and control strategies for…
Connected and automated vehicles (CAVs) have recently gained prominence in traffic research due to advances in communication technology and autonomous driving. Various longitudinal control strategies for CAVs have been developed to enhance…
Recent transportation research highlights the potential of autonomous vehicles (AV) to improve traffic flow mobility as they are able to maintain smaller car-following distances. However, as a unique class of ground robots, AVs are…
The emergence of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic where human-driven vehicles (HDVs) also exist, existing research mostly focuses on "looking ahead" (i.e., the CAVs receive information…
Connected and Automated Vehicles (CAVs) offer a promising solution to the challenges of mixed traffic with both CAVs and Human-Driven Vehicles (HDVs). A significant hurdle in such scenarios is traffic oscillation, or the "stop-and-go"…
We consider a mixed-traffic environment in transportation systems, where Connected and Automated Vehicles (CAVs) coexist with potentially non-cooperative Human-Driven Vehicles (HDVs). We develop a cooperation compliance control framework to…
In mixed-traffic environments, autonomous vehicles (AVs) must interact with heterogeneous human-driven vehicles (HVs) whose intentions and driving styles vary across individuals and scenarios. Such variability introduces uncertainty into…
We derive time and energy-optimal control policies for a Connected Autonomous Vehicle (CAV) to complete lane change maneuvers in mixed traffic. The interaction between CAVs and Human-Driven Vehicles (HDVs) requires designing the best…
Connected and Autonomous Vehicles (CAVs) technology facilitates the advancement of intelligent transportation. However, intelligent control techniques for mixed traffic flow at signalized intersections involving both CAVs and Human-Driven…
In this paper, we investigate the coordination of vehicle maneuvers in mixed-traffic corridors where connected and automated vehicles, human-driven vehicles, and buses interact under dedicated bus lane operations. We develop a segment-based…